# geospatial plotting deps
import branca.colormap as cm
import folium
import geopandas as gpd

import numpy as np
import pandas as pd
pd.set_option("max_rows", None)
from oscovida import fetch_cases, get_population, get_country_data, fetch_cases_last_execution

# get a list of all country names
countries = fetch_cases().index.drop_duplicates()

data = []

for region in countries:
    c, _, _ = get_country_data(region)   # get cumulative infections c
    c = c[-15:]
    try:
        population = get_population(region)
        new_cases = int(c[-1] - c[-15]) 
        incidence = new_cases / population * 100000. 
        data += [(region, population, new_cases, round(incidence, 1))]
    except:
        print(f"Skip {region}")    # skip regions for which we have no population numbers

data.sort(key=lambda x: x[3], reverse=True)

# turn into pandas DataFrame for easier display
table = pd.DataFrame(data, columns=["country", "population", "new cases", "14-day-incidence"]).set_index("country")

# Show last update date
import time
print(f"Last updated {time.asctime()}")

table.sort_index()

table

countries = gpd.read_file("./.country_shapes/countries.shp")
countries = countries.rename(columns={'CNTRY_NAME': 'country'})

countries_geospatial = countries.merge(table, on='country')

countries_geospatial.plot(column='14-day-incidence')

cases, deaths, label = get_country_data("Germany")

c_y = cases[-1]
c_y

c_15 = cases[-15]
c_15

c_new = c_y - c_15 
c_new

population = get_population("Germany")
population

incidence = c_new / (population/100000)
incidence

# For debugging: When was the data downloaded
fetch_cases_last_execution()